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Senior Gen AI/ML Engineer and Data Engineer with 8+ years of experience building production-grade AI/ML, NLP, and Generative AI solutions across highly regulated, data-intensive industries. Skilled in LLM-powered assistants, RAG, semantic search, intelligent document processing, and end-to-end ML lifecycle engineering (data, training, deployment, monitoring, governance). Experienced in cloud-native architectures on Azure/AWS/GCP and in building scalable streaming/batch data platforms with Spark, Kafka, and Databricks. Strong focus on responsible AI (groundedness, hallucination detection, security guardrails, explainability, auditability) and enterprise integration via REST APIs, microservices, and event-driven workflows.…Senior Gen AI/ML Engineer and Data Engineer with 8+ years of experience building production-grade AI/ML, NLP, and Generative AI solutions across highly regulated, data-intensive industries. Skilled in LLM-powered assistants, RAG, semantic search, intelligent document processing, and end-to-end ML lifecycle engineering (data, training, deployment, monitoring, governance). Experienced in cloud-native architectures on Azure/AWS/GCP and in building scalable streaming/batch data platforms with Spark, Kafka, and Databricks. Strong focus on responsible AI (groundedness, hallucination detection, security guardrails, explainability, auditability) and enterprise integration via REST APIs, microservices, and event-driven workflows.

varun vullengala

AI Engineer, Data Engineer, Data Scientist, +2

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Senior Gen AI/ML Engineer and Data Engineer with 8+ years of experience building production-grade AI/ML, NLP, and Generative AI solutions across highly regulated, data-intensive industries. Skilled in LLM-powered assistants, RAG, semantic search, intelligent document processing, and end-to-end ML lifecycle engineering (data, training, deployment, monitoring, governance). Experienced in cloud-native architectures on Azure/AWS/GCP and in building scalable streaming/batch data platforms with Spark, Kafka, and Databricks. Strong focus on responsible AI (groundedness, hallucination detection, security guardrails, explainability, auditability) and enterprise integration via REST APIs, microservices, and event-driven workflows.…Senior Gen AI/ML Engineer and Data Engineer with 8+ years of experience building production-grade AI/ML, NLP, and Generative AI solutions across highly regulated, data-intensive industries. Skilled in LLM-powered assistants, RAG, semantic search, intelligent document processing, and end-to-end ML lifecycle engineering (data, training, deployment, monitoring, governance). Experienced in cloud-native architectures on Azure/AWS/GCP and in building scalable streaming/batch data platforms with Spark, Kafka, and Databricks. Strong focus on responsible AI (groundedness, hallucination detection, security guardrails, explainability, auditability) and enterprise integration via REST APIs, microservices, and event-driven workflows.

Available to hire

Senior Gen AI/ML Engineer and Data Engineer with 8+ years of experience building production-grade AI/ML, NLP, and Generative AI solutions across highly regulated, data-intensive industries. Skilled in LLM-powered assistants, RAG, semantic search, intelligent document processing, and end-to-end ML lifecycle engineering (data, training, deployment, monitoring, governance).

Experienced in cloud-native architectures on Azure/AWS/GCP and in building scalable streaming/batch data platforms with Spark, Kafka, and Databricks. Strong focus on responsible AI (groundedness, hallucination detection, security guardrails, explainability, auditability) and enterprise integration via REST APIs, microservices, and event-driven workflows.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

English

Advanced

Work Experience

Senior Gen AI/ML Engineer at State Farm Insurance

May 1, 2024 - Present

Designed and developed enterprise Generative AI and LLM solutions using Python, Azure OpenAI, Azure AI Foundry, LangChain, LangGraph, and LlamaIndex for underwriting assistance, claims automation, policy analysis, and customer service optimization. Architected scalable RAG platforms using Azure AI Search, Pinecone, embeddings, metadata filtering, and hybrid search. Built production-grade AI agents and conversational assistants integrating with enterprise systems via FastAPI, REST APIs, Redis, and PostgreSQL. Implemented prompt engineering frameworks, fine-tuned open-source LLMs with LoRA/PEFT/QLoRA, and delivered intelligent document understanding pipelines with OCR and semantic indexing. Developed fraud/risk intelligence combining structured insurance data with LLM insights. Created data pipelines with Databricks/Spark/Kafka for ingestion, transformation, and vectorization. Established MLflow-based experiment tracking and model lifecycle management, containerized services with Docker,

Data Scientist/ML Engineer at Tenet Healthcare

February 1, 2022 - April 30, 2024

Designed and deployed production-ready ML models on Azure Machine Learning integrated with Azure OpenAI for clinical decision support. Containerized workloads with Docker and orchestrated them on AKS for scalable inference services. Built RAG solutions using Azure OpenAI and embeddings to help clinicians retrieve medical knowledge and treatment guidelines, including Pinecone-based vector search. Integrated EHR/EMR systems (Epic/Cerner) using HL7 standards and FHIR interoperability to exchange clinical and claims data. Standardized medical coding with ICD-10/CPT and terminology with SNOMED CT. Supported HCC risk adjustment models for value-based care contracts and analytics reporting. Engineered healthcare data pipelines (labs, imaging, monitoring, claims), implemented feature engineering into PostgreSQL/ML frameworks, and delivered real-time patient monitoring alerts. Built clinician-facing apps (React + REST APIs) for document search and summarization. Applied HIPAA-compliant secured

Data Engineer at Albertsons Companies

January 1, 2020 - January 31, 2022

Built product recommendation and analytics solutions using collaborative filtering, XGBoost, and Random Forest; developed clustering and anomaly detection for purchasing patterns and fraud signals (K-Means, Isolation Forest). Engineered scalable ETL/data pipelines with Apache Spark and Hadoop for POS transactions and customer purchase history, including ingestion and transformations from retail systems. Delivered demand forecasting and promotion analytics using ARIMA, regression models, and A/B testing to measure sales lift and support inventory planning. Developed Flask-based APIs to serve analytics to dashboards and applications, and containerized services with Docker for scalable deployment. Integrated ML outputs into CRM/marketing platforms for targeted campaigns and recommendations. Created Tableau dashboards for monitoring sales trends and promotional effectiveness. Automated feature engineering with Python/SQL/Spark and optimized query performance via partitioning/indexing. Impl

Data Engineer at BMO Bank

October 1, 2018 - November 30, 2019

Developed SQL-based ETL pipelines and stored procedures to ingest, transform, and integrate large banking datasets (customer, transactions, loans, deposits, payments) to support analytics and regulatory reporting. Performed EDA with Python/Pandas/NumPy/Matplotlib and built Tableau dashboards for behavioral insights, branch performance, KPIs, and fraud trends. Implemented NLP pipelines using Word2Vec, TF-IDF, and rule-based entity extraction for unstructured banking/compliance documents. Designed reporting and backend data services enabling near real-time visualization in Tableau/Power BI. Built embedding models (Word2Vec) and time-series forecasting (ARIMA/regression) for liquidity forecasting and workload/financial trend analysis. Engineered distributed ETL with Hadoop/Spark/Hive/PySpark including partitioning and incremental loading. Applied data governance, encryption, and RBAC aligned with PCI-DSS, SOX, GLBA and internal compliance policies. Modeled enterprise warehouses using Star

Data Analyst at Nokia Networks

July 1, 2017 - September 30, 2018

Developed interactive Tableau dashboards and automated Excel reporting for network operations, customer care, and sales with performance insights. Migrated legacy Excel/Access reporting into Tableau Server dashboards to improve governance and self-service analytics. Built and maintained reporting datasets using PostgreSQL/MySQL sources for subscriber usage, churn, and revenue analytics. Integrated billing and network performance pipelines into enterprise data warehouse systems for consolidated subscriber and service quality visibility. Wrote complex SQL queries across SQL Server and Oracle for daily/weekly operational reporting. Delivered ad-hoc analytics for faster decisions. Partnered with data engineering on ETL documentation, lineage, and transformation logic. Performed QA validation of dashboard/report outputs to ensure accuracy and consistency. Implemented RBAC in Tableau Server for data security and audit readiness, optimized refresh schedules/SLAs, and trained end users.